Merge pull request #2 from neuralkn0t/twig

Add computation of standard deviation and tSNR as multimodal metrics

Author: smoia

physioqc/metrics/multimodal.py

@@ -1,8 +1,50 @@
 """These functions compute RETROICOR regressors (Glover et al. 2000)."""
+# import file
 import numpy as np
 
 from .. import references
 from ..due import due
 
 
-pass
+def std(signal):  
+    """
+    Calculate standard deviation across input channels of signal.
+    
+    Parameters
+    ----------
+    std : function
+        Calculate standard deviation across input channels.
+    args : signal (X, n) :obj:`numpy.ndarray`
+        ND array with signal of some human biometric data, hopefully from a living human.
+        signal, of shape (n_channels, )
+        
+    Returns
+    -------
+    N-sized array :obj:`numpy.ndarray`
+        Standard deviation of signal.
+    """
+    std_val = np.std(signal, axis=0)
+    return std_val
+
+
+def tSNR(signal):  
+    """
+    Calculate temporal signal to noise ration of signal.
+    
+    Parameters
+    ----------
+    tSNR : function
+        Calculate temporal signal to noise ratio.
+    args : signal
+        ND array with signal of some human biometric data, hopefully from a living human.
+        
+    Returns
+    -------
+    N-sized array :obj:`numpy.ndarray`
+        Temporal signal to noise ratio of signal.
+    """
+    me = np.mean(signal, axis=0)
+    std = np.std(signal, axis=0)
+    tSNR_val = me / std
+    return tSNR_val
+